Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Maziar Sahamkhadam"'
Publikováno v:
Journal of Forest Economics. 38
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c855af172a1de1b521ce4eba7789f6e0
https://doi.org/10.1561/112.00000560
https://doi.org/10.1561/112.00000560
Autor:
Maziar Sahamkhadam
Publikováno v:
Journal of Asset Management. 22:209-223
This study investigates expectile Value-at-Risk (EVaR) as a risk measure in dynamic copula-based portfolio optimization, compared with the common variance and CVaR. To estimate the dependence structure between asset returns, the canonical vine copula
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02e36e04672accf59e4301702c886d7b
https://doi.org/10.1057/s41260-021-00210-8
https://doi.org/10.1057/s41260-021-00210-8
Publikováno v:
International Journal of Finance and Economics
We construct portfolio strategies consisting of different stocks from four main energy market sectors, including oil and gas, oil and gas related equipment and services, multiline utilities, and renewable energy. To construct portfolio strategies, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7d83b3764f5553d2b6eac55b3986412
https://doi.org/10.1002/ijfe.2610
https://doi.org/10.1002/ijfe.2610
Autor:
Maziar Sahamkhadam, Andreas Stephan
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c6f7e6667b4194f24b75df17560a99e
https://doi.org/10.2139/ssrn.4117152
https://doi.org/10.2139/ssrn.4117152
Autor:
Gazi Salah Uddin, Ou Tang, Maziar Sahamkhadam, Farhad Taghizadeh-Hesary, Muhammad Yahya, Pontus Cerin, Jakob Rehmea
Publikováno v:
Revisiting Electricity Market Reforms ISBN: 9789811942655
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f22ee38e52c4e6744c192a1649a554a8
https://doi.org/10.1007/978-981-19-4266-2_5
https://doi.org/10.1007/978-981-19-4266-2_5
Publikováno v:
Finance research letters. 46
Did Corporate Social Responsibility investing benefit shareholders during the COVID-19 pandemic crisis? Distinguishing between downside tail risk and upside reward potential of stock returns, we provide evidence from 5,073 stocks listed on stock mark
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c30a06666a5444f09568c84e8b9928c1
https://pubmed.ncbi.nlm.nih.gov/36569340
https://pubmed.ncbi.nlm.nih.gov/36569340
Autor:
Muhammad Yahya, Jakob Rehme, Ou Tang, Maziar Sahamkhadam, Farhad Taghizadeh-Hesary, Pontus Cerin, Gazi Salah Uddin
Publikováno v:
SSRN Electronic Journal.
Short-term electricity price forecasting has received considerable attention in recent years. Despite this increased interest, the literature lacks a concrete consensus on the most suitable forecasting approach. We conduct an extensive empirical anal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33712afcbc84530d69a817edce9c7945
https://doi.org/10.2139/ssrn.3807052
https://doi.org/10.2139/ssrn.3807052
Publikováno v:
SSRN Electronic Journal.
We extend the Black-Litterman (BL) approach to incorporate tail dependency in portfolio optimization and estimate the posterior joint distribution of returns using vine copulas. Our novel copula-based BL (CBL) model leads to flexibility in modeling r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fbd7dc8377ef5009b9c2e4360f043658
https://doi.org/10.2139/ssrn.3708097
https://doi.org/10.2139/ssrn.3708097
Publikováno v:
International Journal of Forecasting. 34:497-506
This study uses GARCH-EVT-copula and ARMA-GARCH-EVT-copula models to perform out-of-sample forecasts and simulate one-day-ahead returns for ten stock indexes. We construct optimal portfolios based on the global minimum variance (GMV), minimum conditi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c402112f84f8598389bd3e3efb1e87bf
https://doi.org/10.1016/j.ijforecast.2018.02.004
https://doi.org/10.1016/j.ijforecast.2018.02.004
Available online 8 June 2019 We explore the robustness, efficiency and accuracy of the multi-scale forecasting in crude oil markets. We adopt a novel hybrid wavelet auto-ARMA model to detect the inherent nonlinear dynamics of crude oil returns with a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92804c357fea9a98a6363fef0a9efb72
https://hdl.handle.net/1814/66123
https://hdl.handle.net/1814/66123